Cobb Sharon, Bazargan Mohsen, Sandoval Jessica Castro, Wisseh Cheryl, Evans Meghan C, Assari Shervin
School of Nursing, Charles R Drew University of Medicine and Science, Los Angeles, CA 90059, USA.
Department of Family Medicine, Charles R Drew University of Medicine and Science, Los Angeles, CA 90059, USA.
Brain Sci. 2020 Mar 7;10(3):154. doi: 10.3390/brainsci10030154.
It is known that depression remains largely untreated in underserved communities. Hence, it is desirable to gain more knowledge on the prevalence and correlates of untreated depression among African-American (AA) older adults in economically disadvantaged areas. This knowledge may have the public health benefit of improving detection of AA older adults with depression who are at high risk of not receiving treatment, thereby reducing this health disparity.
To study health and social correlates of untreated depression among AA older adults in economically disadvantaged areas.
Between 2015 and 2018, this cross-sectional survey was conducted in South Los Angeles. Overall, 740 AA older adults who were 55+ years old entered this study. Independent variables were age, gender, living arrangement, insurance type, educational attainment, financial strain, chronic medical conditions, and pain intensity. Untreated depression was the dependent variable. Logistic and polynomial regression models were used to analyze these data.
According to the polynomial regression model, factors such as number of chronic medical conditions and pain intensity were higher in individuals with depression, regardless of treatment status. As our binary logistic regression showed, age, education, and number of providers were predictive of receiving treatment for depression.
Age, educational attainment, number of providers (as a proxy of access to and use of care) may be useful to detect AA older adults with depression who are at high risk of not receiving treatment. Future research may focus on decomposition of the role of individual-level characteristics and health system-level characteristics that operate as barriers and facilitators to AA older adults receiving treatment for depression.
众所周知，在服务不足的社区中，抑郁症很大程度上仍未得到治疗。因此，有必要更多地了解经济弱势地区非裔美国（AA）老年人中未经治疗的抑郁症的患病率及其相关因素。这些信息可能对改善对有抑郁症但极有可能无法接受治疗的非裔美国老年人的检测具有公共卫生益处，从而减少这种健康差距。
研究经济弱势地区非裔美国老年人中未经治疗的抑郁症的健康和社会相关因素。
2015年至2018年期间，在洛杉矶南部进行了这项横断面调查。共有740名年龄在55岁及以上的非裔美国老年人参与了本研究。自变量包括年龄、性别、居住安排、保险类型、教育程度、经济压力、慢性疾病状况和疼痛强度。未经治疗的抑郁症是因变量。使用逻辑回归和多项式回归模型分析这些数据。
根据多项式回归模型，无论治疗状况如何，抑郁症患者的慢性疾病数量和疼痛强度等因素都更高。正如我们的二元逻辑回归所示，年龄、教育程度和医疗服务提供者数量可预测是否接受抑郁症治疗。
年龄、教育程度、医疗服务提供者数量（作为获得和使用医疗服务的一个指标）可能有助于检测出极有可能无法接受治疗的患有抑郁症的非裔美国老年人。未来的研究可侧重于剖析个体层面特征和卫生系统层面特征所起的作用，这些特征对非裔美国老年人接受抑郁症治疗起到阻碍或促进作用。
